Machine Vision And Aoi Sr Engineer Jobs

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: As a Performance Engineer in the Pre-Training team you will be responsible for optimizing the performance of our advanced language models and systems. Their primary focus is on improving key model training metrics, such as training throughput, ensuring high accelerator utilization. The team combines expertise in software engineering, machine learning, and low-level kernel design and development to design robust systems and enhance model performance. You will work on identifying and removing performance bottlenecks, develop cutting-edge training and profiling tools to help Cohere's mission of providing efficient and reliable language understanding and generation capabilities and drive innovation in the field of natural language processing. Note: We have offices in London, Toronto, New York and San Francisco, but we’re also remote-friendly! This team operates primarily between ET to CET time zones, so we’re seeking candidates in locations that align with these hours for effective collaboration. Key Responsibilities: Design and write high-performant and scalable software for training. Understand architectural modific

Zoox is developing state-of-the-art autonomous vehicle software for our purpose-built vehicle. We believe that developing the end-to-end product will get us to market faster and result in a superior customer experience. The Developer Experience team at Zoox is dedicated to improving the process of developing autonomy software, services, and applications. We define and enforce the best practices for engineering across the company. Our approach involves using established programming languages, and tools and, when necessary, developing our own. We're leveraging Large Language Models (LLMs) to improve development velocity and streamline engineering workflows. We're looking for an engineer with firsthand experience as a full-stack developer, who knows the engineering challenges at scale and feels comfortable designing and implementing solutions to address them. In this role, you will: Architect and implement LLM-powered solutions using frontier models like Claude, Gemini, GPT. Build tools that leverage AI and improve engineer productivity by 10x through intelligent code assistance, automated code review, and improving zoox’s operational efficiency. Develop systems to automate mundane development tasks like boilerplate generation, test creation, and code refactoring. Create intelligent workflows that leverage LLMs for bug detection, security vulnerability assessment, and code optimization. Bridge the divide between developers' needs and infrastructure solutions while establishing best practices for responsible AI integration in our development pipeline. Qualifications Bachelor's or Master's degree in Computer Science, Engineering, or a related field with 7+ years of industry experience. Solid experience as a full-stack or backend developer, showcasing a deep understanding of system design, data structures, and algorithms. Fluency in at least one of the following languages: Python or C++. Exper

About Us At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. About the Team The Python Open Source team maintains and evolves the core LangChain Python ecosystem used by millions of developers worldwide. We focus on building reliable, well-designed abstractions for developing AI agents and integrating them with real-world tools and systems. The team works closely with the open-source community, incorporating feedback and contributions while ensuring the core libraries remain stable, scalable, and production-ready. Our work defines the developer experience for building AI applications with Python. About the role In person 5 days/week in San Francisco, CA or Boston, MA (SF preferred) We’re looking to add a core maintainer to the LangChai

About the Team Our Inference team brings OpenAI’s most capable research and technology to the world through our products. We empower consumers, enterprise and developers alike to use and access our start-of-the-art AI models, allowing them to do things that they’ve never been able to before. We focus on performant and efficient model inference, as well as accelerating research progression via model inference. About the Role We are looking for an engineer who wants to take the world's largest and most capable AI models and optimize them for use in a high-volume, low-latency, and high-availability production and research environment. In this role, you will: Work alongside machine learning researchers, engineers, and product managers to bring our latest technologies into production. Work alongside researchers to enable advanced research through awesome engineering. Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of our model inference stack. Build tools to give us visibility into our bottlenecks and sources of instability and then design and implement solutions to address the highest priority issues. Optimize our code and fleet of Azure VMs to utilize every FLOP and every GB of GPU RAM of our hardware. You might thrive in this role if you: Have an understanding of modern ML architectures and an intuition for how to optimize their performance, particularly for inference. Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done. Have at least 5 years of professional software engineering experience. Have or can quickly gain familiarity with PyTorch, NVidia GPUs and the software stacks that optimize them (e.g. NCCL, CUDA), as well as HPC technologies such as InfiniBand, MPI, NVLink, etc. Have experience architecting, building, observing, and debugging production distributed systems. Bonus point if worked on performance-critical distributed systems. Have need

About the Team The Safety Systems team is responsible for various safety work to ensure our best models can be safely deployed to the real world to benefit the society, and is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. The Safety Oversight Research team aims to fundamentally advance our capabilities to maintain oversight over frontier AI models, and leverage these advances to ensure OpenAI’s deployed models are safe and beneficial. This requires a breadth of new ML research in the areas of human-AI collaboration, reasoning, robustness, and scalable oversight to keep pace with model capabilities. We invest heavily in developing novel model and system-level methods of identifying and mitigating AI misuse and misalignment. Our goal is to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. About the Role OpenAI is seeking a senior researcher with a passion for AI safety and experience in safety research. Your role will set directions for research to maintain effective oversight of safe AGI and work on research projects to identify and mitigate misuse and misalignment in our AI systems. You will play a critical role in defining how a safe AI system should look in the future at OpenAI, making a significant impact on our mission to build and deploy safe AGI. In this role, you will: Develop and refine AI monitor models to detect and mitigate known and emerging patterns of misuse and misalignment. Set research directions and strategies to make our AI systems safer, more aligned, and more robust. Evaluate and design effective red-teaming pipelines to examine the end-to-end robustness of our safety systems, and identify areas for future improvement. Conduct research to improve models’ ability to reason about questions of human values, and apply these improved models to practical safety challen

P-1360 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. As a software engineer with a backend focus, you will work with your team to build infrastructure for the Databricks platform at scale. The impact you'll have: Our backend teams cover a diverse range of domains, from core compute fabric resource management to service platforms and machine learning infrastructure. For example, you might work on challenges such as: Supporting Databricks' growth by building foundational infrastructure platforms that enable seamless operation across numerous geographic regions and cloud providers. Implementing cloud-agnostic infrastructure abstractions to help Databricks engineers more efficiently manage and operate their services. Develop tools and processes that drive engineering efficiency at Databricks. We enhance the developer experience for Databricks engineers across various areas, including programming languages, linters, static analysis, IDEs, remote development environments, automated release pipelines, and test automation frameworks. Our current focus is on optimizing the Rust development experience across the organization. What we look for: 2+ years of professional software development experience, or alternatively a PhD degree. Bachelor’s degree or higher in Computer Science, related field, or equivalent experience. Proficiency in one or more backend languages such as Java, Scal

Join Artefact Belgium: Lead the Future of Generative AI and Large Language Models Are you a seasoned AI professional with a passion for generative AI and Large Language Models (LLMs)? Artefact Belgium is looking for a Senior Data Scientist - Gen AI to drive innovation and lead cutting-edge projects. If you have at least four years of experience in AI and consulting, combined with a talent for project and team management, we invite you to shape the future of LLM-driven solutions with us in Brussels. Who You Are Experienced professional: At least 4 years of experience in AI, with a strong background in consulting and delivering impactful projects for diverse clients. Leader and collaborator: Proven experience managing teams, guiding junior colleagues, and fostering collaboration in multidisciplinary environments. Innovative thinker: Able to identify emerging trends in generative AI and apply them to real-world challenges. Results-oriented: Comfortable handling end-to-end project delivery, from ideation and development to deployment and client engagement. Eager to grow: Passionate about advancing your expertise in LLMs and generative AI while mentoring others. Who We Are Artefact is a leading Data & AI consulting firm at the forefront of AI innovation. With a global presence, we collaborate with top-tier clients across industries, including healthcare, manufacturing, and media, to harness the transformative power of generative AI. Our team in Belgium is specialized in LLM and GenAI projects, working on the most advanced applications of these technologies. Our inclusive and forward-thinking culture encourages creativity, collaboration, and professional growth. What You Will Do Lead and deliver LLM projects: Manage the design, development, and deployment of advanced LLM-powered solutions, including RAG systems, agentic AI architectures, and multi-modal applications for our clients. Drive technical excellence: Architect and deploy advanced AI systems leveraging cuttin

Why Work With Us Solve impactful problems. At Seven Research, our close-knit team unites brilliant minds passionate about pushing technological and scientific boundaries in the global markets. We provide state-of-the-art resources and cultivate intellectual freedom, enabling our people to develop groundbreaking solutions to the most complex challenges of our field. Our collaborative approach celebrates excellence from everyone, regardless of tenure. Your Role Our Quantitative Researchers are the intellectual architects of our trading strategies, responsible for developing sophisticated models that transform complex datasets into actionable insights. You will apply rigorous statistical and machine-learning methodologies to diverse financial datasets, develop innovative approaches to understand risk and returns, and design strategy frameworks leveraging first principles from economics and other fields. What We’re Looking For We seek ambitious and talented problem-solvers with strong quantitative backgrounds. No financial knowledge is expected. Quantitative Researcher candidates should have demonstrated capability in conducting cutting-edge research and analysis. We value team members who communicate clearly, have strong critical analysis skills, and can exercise ownership over projects. If working on challenging quantitative problems in a close-knit setting excites you, we’d love to get to know you. The ideal candidate will possess most of the following: PhD, master’s, or bachelor’s degree in computer science, statistics, physics, or a related quantitative field Intellectual curiosity and passion to uncover the inner workings of the global markets Proven track record developing sophisticated predictive models Strong programming skills, including mastery of Python for data analysis Knowledge of statistical and machine learning modeling frameworks Strong problem-solving skills and research acumen Strong communication skills to articulate complex technical concepts Exper

Company Overview Accordion works at the intersection of sponsors and management teams throughout every stage of the investment lifecycle, providing hands-on, execution-focused support to elevate data and analytics capabilities. So, what does it mean to work at Accordion? It means joining 1,000+ analytics, data science, finance & technology experts in a high-growth, agile, and entrepreneurial environment while transforming how portfolio companies drive value. It also means making your mark on Accordion’s future—by embracing a culture rooted in collaboration and a firm-wide commitment to building something great, together. Headquartered in New York City with 10 offices worldwide, Accordion invites you to join our journey. Data & Analytics (Accordion | Data & Analytics) Accordion's Data & Analytics (D&A) team delivers cutting-edge, intelligent solutions to a global clientele, leveraging a blend of domain knowledge, sophisticated technology tools, and deep analytics capabilities to tackle complex business challenges. We partner with Private Equity clients and their Portfolio Companies across diverse sectors, including Retail, CPG, Healthcare, Media & Entertainment, Technology, and Logistics. D&A team delivers data and analytical solutions designed to streamline reporting capabilities and enhance business insights across vast and complex data sets ranging from Sales, Operations, Marketing, Pricing, Customer Strategies, and more. Role Overview: As Manager - Data Science you will be leading one or more client projects to deliver various Advance Analytic solutions. (S)he would be working directly with the clients and guide the team in building a robust solution solving client’s business problem as per agreed timelines through application of business knowledge, project management and technical expertise. What You will do: We expect you to manage a team and work on complex, cross-functional analytical and research-oriented projects us

Company Overview Accordion works at the intersection of sponsors and management teams throughout every stage of the investment lifecycle, providing hands-on, execution-focused support to elevate data and analytics capabilities. So, what does it mean to work at Accordion? It means joining 1,000+ analytics, data science, finance & technology experts in a high-growth, agile, and entrepreneurial environment while transforming how portfolio companies drive value. It also means making your mark on Accordion’s future—by embracing a culture rooted in collaboration and a firm-wide commitment to building something great, together. Headquartered in New York City with 10 offices worldwide, Accordion invites you to join our journey. Data & Analytics (Accordion | Data & Analytics) Accordion's Data & Analytics (D&A) team delivers cutting-edge, intelligent solutions to a global clientele, leveraging a blend of domain knowledge, sophisticated technology tools, and deep analytics capabilities to tackle complex business challenges. We partner with Private Equity clients and their Portfolio Companies across diverse sectors, including Retail, CPG, Healthcare, Media & Entertainment, Technology, and Logistics. D&A team delivers data and analytical solutions designed to streamline reporting capabilities and enhance business insights across vast and complex data sets ranging from Sales, Operations, Marketing, Pricing, Customer Strategies, and more. Role Overview: As Director - Data Science you will be leading one or more client projects to deliver various Advance Analytic solutions. (S)he would be working directly with the clients and guide the team in building a robust solution solving client’s business problem as per agreed timelines through application of business knowledge, project management and technical expertise. What You will do: We expect you to manage a team and work on complex, cross-functional analytical and research-oriented projects u

About Cubist Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. Role: A new Cubist portfolio management team specializing in the systematic trading of equities is looking for a Quant Researcher whose core focus will be working on mid-frequency alpha strategies. Joining the team will provide a unique opportunity to be involved with the early stages of a product launch and develop within a growing team. Responsibilities: Perform rigorous and innovative research to discover systematic anomalies in the equities market End-to-end development, including alpha idea generation, data processing, strategy backtesting, optimization, and production implementation Identify and evaluate new datasets for stock return prediction Maintain and improve portfolio trading in a production environment Contribute to the analysis framework for scalable research Requirements: MS or PhD in a quantitative discipline 0-2 years of professional work experience A background in financial markets is not necessary, but an interest in the field is essential Proven expertise in Python and handling large datasets Fluency in data science practices, e.g., feature engineering. Experience with machine learning is a plus Highly motivated, curious, and critical thinker Collaborative mindset with strong independent research abilities Commitment to the highest ethical standards

ABOUT CUBIST Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. ROLE The candidate will be responsible for some or all of parts of the research pipeline—including data processing, feature design, model training, portfolio construction and management, back-testing, and performance analysis. Successful researchers combine statistical analysis, machine learning techniques, intense passion, and curiosity to decipher the market, and aspire to gain great intellectual understanding and financial outperformance. RESPONSIBILITIES Finding alphas in global equity markets by applying rigorous statistical analysis on technical data or alternative data sets. Performing hypotheses testing, feature design, and backtesting to improve on alpha ideas. Maintaining and improving the research pipeline, including alpha generation, portfolio construction, back-testing, and monetization. Maintaining and improving portfolio trading in production environments. REQUIREMENTS Bachelors degree or higher in mathematics, statistics, computer science, or other quantitative discipline. 2+ years of experience in quantitative research. Experience in medium frequency equity research is a plus. Strong analytical and quantitative skills; solid knowledge in statistics, linear algebra, or machine learning. Proficiency in Python. Familiarity with scientific toolkits, such as Numpy and Pandas. Ability to work both independently and collaboratively within a team. Commitment to the highest ethical standards.

About the Team Our Data Science team is the Avengers to Meesho’s S.H.I.E.L.D 🛡️. And why not? We are the ones who assemble during the toughest challenges and devise creative solutions, building intelligent systems for millions of our users looking at a thousand different categories of products. We’ve barely scratched the surface, and have amazing challenges in charting the future of commerce for Bharat. About the Role As a Principal Data Scientist in our AdTech team, you’ll drive innovation in our advertising platform using advanced machine learning and statistical methods. You’ll tackle complex problems in real-time bidding, ad ranking optimization, budget efficiency, and performance measurement that directly impact our business’s bottom line. This role requires technical excellence and business acumen and you’ll collaborate with cross-functional teams to transform data insights into actionable strategies that enhance our advertising ecosystem. What you will do Design and develop sophisticated bidding, budget pacing and other algorithms that optimize ad spend or ROI. Create frameworks and experimental design to measure ad effectiveness and ROI. Collaborate with product and engineering teams to translate business requirements into efficient AI/ML solutions. Communicate long-term roadmap, insights and recommendations to tech and business leadership. Mentor junior data scientists and provide technical guidance. Lead research initiatives in machine learning, auction theory and advertising technology. What you will need B.Tech in Computer Science, Machine Learning, or a related field with at least 6+ years of experience in AI/ML research. Experience in auction theory, predictive modelling, causal inference, and reinforcement learning. Expertise in PyTorch or TensorFlow, and proficiency in Python as we

About Cubist Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. Role Quantitative researcher to help build out a systematic macro (futures, FX, and vol) strategies. Core focus will be working on mid-frequency alpha strategies. Job Description Develop systematic trading models across FX, commodities, fixed income, and equity markets Alpha idea generation, backtesting, and implementation Assist in building, maintenance, and continual improvement of production and trading environments Evaluate new datasets for alpha potential Improve existing strategies and portfolio optimization Execution monitoring Be a core contributor to growing the investment process and research infrastructure of the team Desirable Candidates Masters or PhD in mathematics, statistics, physics or other quantitative discipline. PhD in statistics or machine learning is a plus Experience in quantitative trading, ideally in FX or futures Experience with alpha research, portfolio construction and optimization Experience building statistical/technical, fundamental, and data driven signals Experience synthesizing predictive signals for both cross-sectional and time-series models Strong experience with data exploration, dimension reduction, and feature engineering Thorough understanding of and comfort using a variety of regression techniques—including OLS, MLS, Ridge, Lasso, and Bayesian inference—as well as techniques for dealing with errors that can occur, such as auto-correlation and heteroskedasticity Experience managing and running risk is a strong plus Proficiency in Python using the machine learning stack—numpy, pandas, scikit-learn, etc. Creative mindset Strong time management abi

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Stripe Infrastructure is responsible for the reliability, scale, performance, and cost of Stripe's systems and the productivity and sentiment of Stripe's people. You may work on a wide variety of critical business areas including: Core Infrastructure—We're the home for Stripe's critical tier0 infrastructure systems (Compute, Networking, DocumentDB, Distributed Caching and High assurance engineering). We build the foundational platform for Stripe products and services to allow them to operate at scale. We drive reliability, availability, efficiency, and scalability of these systems. Developer Infrastructure—We're responsible for the productivity of all developers at Stripe. Ensure Stripe's engineers have a reliable, fast, and easy-to-use inner dev loop to maximize productivity while building everything from low-latency microservices to large-scale data pipelines and machine learning models. Data Infrastructure—We're responsible for offering data serving infrastructure spanning across data warehouse analytics, streaming analytics, and search capabilities. The stack is supported by a collection of internally developed large-scale distributed services and several popular open-source technologies like Trino/Presto, Apache Pinot, Hive Metastore, ElasticSearch etc. The systems we own support all of the data serving needs of high-scale services and thousands of individual Stripes across the company. Admin Platform—We empower Stripes to quickly